ReviewAnnual review of physical chemistry2011
Lessons in fluctuation correlation spectroscopy.
Review in Annual review of physical chemistry, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 89 papers.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
89 citing papers in PubMed, 215 citations in OpenAlex.
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- Article
29 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Molecular diffusion and transport processes are fundamental in physical, chemical, and biological systems. Current approaches to measuring molecular transport in cells and tissues based on perturbation methods, e.g., fluorescence recovery after photobleaching, are invasive; single-point fluctuation correlation methods are local; and single-particle tracking requires the observation of isolated particles for relatively long periods of time. We discuss here the detection of molecular transport by exploiting spatiotemporal correlations measured among points at large distances (>1 μm). We illustrate the evolution of the conceptual framework that started with single-point fluorescence fluctuation analysis based on the transit of fluorescent molecules through a small volume of illumination. This idea has evolved to include the measurement of fluctuations at many locations in the sample using microscopy imaging methods. Image fluctuation analysis has become a rich and powerful technique that can be used to extract information about the spatial distribution of molecular concentration and transport in cells and tissues.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.